本文選題：分布式城市需水預(yù)測(cè)模型　切入點(diǎn)：建設(shè)用地　出處：《中國(guó)水利水電科學(xué)研究院》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：城市需水量的預(yù)測(cè)在城市供排水網(wǎng)絡(luò)規(guī)劃中具有重要意義。傳統(tǒng)的需水預(yù)測(cè)方法包括水量指標(biāo)法和概率統(tǒng)計(jì)法及系統(tǒng)工程模型廣泛應(yīng)用于城市需水量的預(yù)測(cè),但存在一些不足之處。利用不同水量指標(biāo)法預(yù)測(cè)得到的城市需水量結(jié)果差別較大,水量指標(biāo)的選取具有一定的主觀性。概率統(tǒng)計(jì)法及系統(tǒng)工程模型預(yù)測(cè)得到的城市需水量結(jié)果空間尺度有限,難以滿足城市供排水網(wǎng)絡(luò)規(guī)劃的要求。城市建設(shè)用地需水過程和城市建設(shè)用地單元類型密切相關(guān),不同建設(shè)用地類型之間對(duì)水資源的需求強(qiáng)度存在顯著差異。文章基于八類城市建設(shè)用地類型與三類主要城市需水類型的空間聯(lián)系,利用城市歷年土地利用數(shù)據(jù)、人口數(shù)據(jù)及需水量數(shù)據(jù),建立了分布式的城市需水預(yù)測(cè)模型。文章應(yīng)用分布式城市需水預(yù)測(cè)模型對(duì)廈門市2020年城市需水量進(jìn)行了預(yù)測(cè),利用PEST軟件率定了廈門市建設(shè)用地單元的需水參數(shù),分析了參數(shù)的合理性,預(yù)測(cè)得到了廈門市2020年城市建成區(qū)的需水量及其空間分布。結(jié)果表明廈門市2020年的城市需水總量將達(dá)到36657萬(wàn)噸,比2014年增長(zhǎng)24.17%;居民用地和工業(yè)用地的需水強(qiáng)度大于其他建設(shè)用地類型,廈門島內(nèi)居民用地的需水強(qiáng)度遠(yuǎn)大于廈門市其他行政區(qū)居民用地的需水強(qiáng)度;廈門市城市建成區(qū)需水量的空間分布與人口密度具有很好的相關(guān)性,不同建設(shè)用地類型上需水強(qiáng)度差異明顯。此外,文章利用分布式城市需水預(yù)測(cè)模型預(yù)測(cè)得到的廈門市2020年城市建成區(qū)需水量數(shù)據(jù),選取廈門島內(nèi)的一片城市典型匯水區(qū),計(jì)算了典型匯水區(qū)內(nèi)的自然排水量及人工排水量,并根據(jù)典型匯水區(qū)的自然排水量及人工排水量數(shù)據(jù)計(jì)算了典型匯水區(qū)雨污分流制管網(wǎng)及雨污合流制管網(wǎng)模式下的污水管網(wǎng)排水量。
[Abstract]:The prediction of urban water demand is of great significance in urban water supply and drainage network planning. Traditional water demand forecasting methods include water quantity index method, probability statistics method and system engineering model, which are widely used in urban water demand prediction. However, there are some shortcomings. The results of urban water demand predicted by different water index methods are quite different. The selection of water demand index is subjective. The spatial scale of urban water demand predicted by probabilistic statistical method and system engineering model is limited. It is difficult to meet the requirements of urban water supply and drainage network planning. The process of water demand for urban construction land is closely related to the type of urban construction land unit. There are significant differences in the demand intensity of water resources among different types of construction land. Based on the spatial relationship between the eight types of urban construction land types and the three main types of urban water demand, the paper makes use of the land use data of past years. Based on the population data and water demand data, a distributed urban water demand forecasting model is established in this paper. In 2020, the urban water demand of Xiamen is forecasted by using the distributed urban water demand forecasting model. The water requirement parameters of construction land units in Xiamen are determined by using PEST software, and the rationality of the parameters is analyzed. The water demand and its spatial distribution of the urban built-up area in Xiamen on 2020 are predicted. The results show that the total water demand of Xiamen on 2020 will reach 366.57 million tons. Compared with 2014, the water demand intensity of residential land and industrial land is higher than that of other types of construction land, and the water demand intensity of residential land in Xiamen Island is much higher than that of residential land in other districts of Xiamen. There is a good correlation between the spatial distribution of water demand and population density in urban built-up areas of Xiamen, and there are obvious differences in water demand intensity among different construction land types. Based on the water demand data of urban built-up area in Xiamen in 2020, a typical catchment area in Xiamen Island is selected, and the natural and artificial water discharges in typical catchment area are calculated. According to the data of natural and artificial drainage in typical catchment area, the drainage capacity of sewage pipe network in typical catchment area is calculated.
【學(xué)位授予單位】：中國(guó)水利水電科學(xué)研究院
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TV213.4

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 周晉軍;劉家宏;董慶珊;王忠靜;王浩;向晨瑤;欒勇;;城市耗水計(jì)算模型[J];水科學(xué)進(jìn)展;2017年02期

2 楊舒媛;王軍;魏保義;楊東方;;城市需水預(yù)測(cè)方法綜述及應(yīng)用調(diào)研[J];北京規(guī)劃建設(shè);2016年04期

3 范江;杜坤;周明;劉月;;考慮環(huán)境因子的市政消防用水量計(jì)算[J];低溫建筑技術(shù);2016年03期

4 楊冀紅;郭蕾;孫家波;趙冬玲;史良樹;戰(zhàn)鷹;張超;;利用SPOT-6影像提取新增建設(shè)用地的方法研究[J];地理信息世界;2014年04期

5 程曉光;張靜;宮輝力;;半干旱半濕潤(rùn)地區(qū)HSPF模型水文模擬及參數(shù)不確定性研究[J];環(huán)境科學(xué)學(xué)報(bào);2014年12期

6 劉家宏;王建華;李海紅;李悅;;城市生活用水指標(biāo)計(jì)算模型[J];水利學(xué)報(bào);2013年10期

7 張文中;李正兆;;城市工業(yè)用水量指標(biāo)取值探討[J];山西建筑;2012年27期

8 黃德治;;變化環(huán)境下城市需水量影響因子識(shí)別[J];中國(guó)農(nóng)村水利水電;2012年03期

9 張志果;邵益生;徐宗學(xué);;基于恩格爾系數(shù)與霍夫曼系數(shù)的城市需水量預(yù)測(cè)[J];水利學(xué)報(bào);2010年11期

10 史瑞蘭;孫照東;劉永峰;鄭建國(guó);李銳;;對(duì)我國(guó)開展規(guī)劃水資源論證的幾點(diǎn)認(rèn)識(shí)[J];人民黃河;2009年06期

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